GestureRecognitionToolkit  Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
FeatureExtraction Member List

This is the complete list of members for FeatureExtraction, including all inherited members.

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
BaseTypes enum name (defined in MLBase)MLBase
CLASSIFIER enum value (defined in MLBase)MLBase
classType (defined in GRTBase)GRTBaseprotected
clear()FeatureExtractionvirtual
CLUSTERER enum value (defined in MLBase)MLBase
computeFeatures(const VectorFloat &inputVector)FeatureExtractioninlinevirtual
computeFeatures(const MatrixFloat &inputMatrix)FeatureExtractioninlinevirtual
copyBaseVariables(const FeatureExtraction *featureExtractionModule)FeatureExtraction
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
createInstanceFromString(const std::string &featureExtractionType) (defined in FeatureExtraction)FeatureExtractionstatic
createNewInstance() const FeatureExtraction
debugLog (defined in GRTBase)GRTBaseprotected
deepCopyFrom(const FeatureExtraction *rhs)FeatureExtractioninlinevirtual
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
featureDataReady (defined in FeatureExtraction)FeatureExtractionprotected
FeatureExtraction()FeatureExtraction
featureExtractionType (defined in FeatureExtraction)FeatureExtractionprotected
featureMatrix (defined in FeatureExtraction)FeatureExtractionprotected
featureVector (defined in FeatureExtraction)FeatureExtractionprotected
getBaseType() const MLBase
getClassType() const GRTBase
getFeatureDataReady() const FeatureExtraction
getFeatureExtractionType() const FeatureExtraction
getFeatureMatrix() const FeatureExtraction
getFeatureVector() const FeatureExtraction
getGRTBasePointer()GRTBase
getGRTBasePointer() const GRTBase
getGRTRevison()GRTBasestatic
getGRTVersion(bool returnRevision=true)GRTBasestatic
getInitialized() const FeatureExtraction
getInputType() const MLBase
getIsBaseTypeClassifier() const MLBase
getIsBaseTypeClusterer() const MLBase
getIsBaseTypeRegressifier() const MLBase
getLastErrorMessage() const GRTBase
getLastInfoMessage() const GRTBase
getLastWarningMessage() const GRTBase
getLearningRate() const MLBase
getMap() (defined in FeatureExtraction)FeatureExtractioninlineprotectedstatic
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getModelTrained() const MLBase
getNumInputDimensions() const FeatureExtraction
getNumInputFeatures() const MLBase
getNumOutputDimensions() const FeatureExtraction
getNumTrainingIterationsToConverge() const MLBase
getOutputType() const MLBase
getRandomiseTrainingOrder() const MLBase
getRootMeanSquaredTrainingError() const MLBase
getScalingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingResults() const MLBase
getUseValidationSet() const MLBase
getValidationSetAccuracy() const MLBase
getValidationSetPrecision() const MLBase
getValidationSetRecall() const MLBase
getValidationSetSize() const MLBase
GRT_DEPRECATED_MSG("saveModelToFile(std::string filename) is deprecated, use save(std::string filename) instead", virtual bool saveModelToFile(std::string filename) const )MLBase
GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )MLBase
GRT_DEPRECATED_MSG("loadModelFromFile(std::string filename) is deprecated, use load(std::string filename) instead", virtual bool loadModelFromFile(std::string filename))MLBase
GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))MLBase
GRTBase(void)GRTBase
infoLog (defined in GRTBase)GRTBaseprotected
init()FeatureExtractionprotected
initialized (defined in FeatureExtraction)FeatureExtractionprotected
inputType (defined in MLBase)MLBaseprotected
learningRate (defined in MLBase)MLBaseprotected
load(const std::string filename)MLBasevirtual
load(std::fstream &file)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)MLBaseprotected
loadFeatureExtractionSettingsFromFile(std::fstream &file)FeatureExtractionprotected
loadModelFromFile(std::fstream &file)FeatureExtractioninlinevirtual
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
MLBase(void)MLBase
notify(const TrainingResult &data) (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
notify(const TestInstanceResult &data) (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual
notifyTestResultsObservers(const TestInstanceResult &data)MLBase
notifyTrainingResultsObservers(const TrainingResult &data)MLBase
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
outputType (defined in MLBase)MLBaseprotected
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)MLBasevirtual
predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const MLBasevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
registerTestResultsObserver(Observer< TestInstanceResult > &observer)MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)MLBase
REGRESSIFIER enum value (defined in MLBase)MLBase
removeAllTestObservers()MLBase
removeAllTrainingObservers()MLBase
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)MLBase
reset()FeatureExtractioninlinevirtual
rootMeanSquaredTrainingError (defined in MLBase)MLBaseprotected
save(const std::string filename) const MLBasevirtual
save(std::fstream &file) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const MLBaseprotected
saveFeatureExtractionSettingsToFile(std::fstream &file) const FeatureExtractionprotected
saveModelToFile(std::fstream &file) const FeatureExtractioninlinevirtual
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)MLBaseinline
setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
setInfoLoggingEnabled(const bool loggingEnabled)GRTBase
setLearningRate(const Float learningRate)MLBase
setMaxNumEpochs(const UINT maxNumEpochs)MLBase
setMinChange(const Float minChange)MLBase
setMinNumEpochs(const UINT minNumEpochs)MLBase
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setTrainingLoggingEnabled(const bool loggingEnabled)MLBase
setUseValidationSet(const bool useValidationSet)MLBase
setValidationSetSize(const UINT validationSetSize)MLBase
setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
StringFeatureExtractionMap typedefFeatureExtraction
testingLog (defined in GRTBase)GRTBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)MLBasevirtual
train(TimeSeriesClassificationData trainingData)MLBasevirtual
train(ClassificationDataStream trainingData)MLBasevirtual
train(UnlabelledData trainingData)MLBasevirtual
train(MatrixFloat data)MLBasevirtual
train_(ClassificationData &trainingData)MLBasevirtual
train_(RegressionData &trainingData)MLBasevirtual
train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
train_(ClassificationDataStream &trainingData)MLBasevirtual
train_(UnlabelledData &trainingData)MLBasevirtual
train_(MatrixFloat &data)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
trainingResults (defined in MLBase)MLBaseprotected
trainingResultsObserverManager (defined in MLBase)MLBaseprotected
useScaling (defined in MLBase)MLBaseprotected
useValidationSet (defined in MLBase)MLBaseprotected
validationSetAccuracy (defined in MLBase)MLBaseprotected
validationSetPrecision (defined in MLBase)MLBaseprotected
validationSetRecall (defined in MLBase)MLBaseprotected
validationSetSize (defined in MLBase)MLBaseprotected
warningLog (defined in GRTBase)GRTBaseprotected
~FeatureExtraction()FeatureExtractionvirtual
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual